Automatic Phonetic Segmentation for a Speech Corpus of Hebrew
نویسندگان
چکیده
This paper presents our study on different phonetic segmentation methods based on hidden Markov models evaluated against a Hebrew speech corpus. We investigated methods for fully automatic phonetic segmentation using only the corpus which should be segmented and automatically generated phonetic transcriptions. A new method for phonetic boundary correction based on spectral variation of the speech signal is proposed. The proposed method increased the boundary correctness of the baseline HMM segmentation system from 30.2%, 59.5% and 86.2% of automatic boundary marks with error smaller than 5, 10 and 20 ms respectively, to 52.3%, 76.3% and 90.7%.
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